Vajira was the first PhD student to graduate from the PhD program for Engineering Science at OsloMet and SimulaMet, supervised by Chief Research Scientist Michael A. Riegler, Professor Pål Halvorsen, and Professor Hugo Hammer. 

In his thesis, he presents a novel framework that overcomes some of the inherent restrictions and limitations of medical data by using deep generative adversarial networks to produce synthetic data with characteristics similar to the real data, so-called DeepSynth (deep synthetic) data.

The results indicate that the framework, titled DeepSynthBody, may be a solution to solve key issues associated with medical data, namely privacy concerns and the high cost of annotations. 

DeepSynthBody: the beginning of the end for data deficiency in medicine is available through this link. 

– I am so honoured to have received this award. The award is not only for me; it is for all my supervisors and contributors to our research studies, says Vajira on the achievement. 

The paper was submitted to the 2021 TCCLS PhD Thesis awards, and selected as one of two awardees. 

Vajira will receive the award during the 35th IEEE Symposium on Computer-Based Medical Systems.